Kotlin mathematics extensions library
Go to file
2018-08-03 09:51:54 +03:00
kmath-common Ddded kmath prefix to module names. 2018-08-03 09:07:35 +03:00
kmath-jvm Ddded kmath prefix to module names. 2018-08-03 09:07:35 +03:00
.gitignore Initial commit. Algebra operations. NDArray 2018-04-22 16:03:05 +03:00
build.gradle Added operations with external functions and elements on NDArray. Switched to kotlin 1.2.60 2018-08-03 09:04:39 +03:00
LICENSE Initial commit 2018-04-14 08:52:49 +03:00
README.md Update README.md 2018-08-03 09:51:54 +03:00
settings.gradle Ddded kmath prefix to module names. 2018-08-03 09:07:35 +03:00

KMath

Kotlin MATHematics library is intended as a kotlin based analog of numpy python library. Contrary to numpy and scipy it is modular and has a lightweight core.

Features

  • Algebra
    • Mathematical operation entities like rings, spaces and fields with (TODO add example to wiki)
    • Basic linear algebra operations (summs products, etc) backed by Space API.
    • Complex numbers backed by Field API (meaning that they will be useable in any structures like vectors and NDArrays).
    • [In progress] advanced linear algebra operations like matrix inversions.
  • Array-like structures Full support of numpy-like ndarray including mixed ariphmetic operations and function operations on arrays and numbers just like it works in python (with benefit of static type checking).

Multi-platform support

KMath is developed as a multi-platform library, which means that most of interfaces are declared in common module. Implementation is also done in common module wherever it is possible. In some cases features are delegated to platform even if they could be done in common module because of platform performance optimization.

Performance

The calculation performance is one of major goals of KMath in the future, but in some cases it is not possible to achieve both performance and flexibility. We expect to firstly focus on creating convenient universal API and then work on increasing performance for specific cases. We expect the worst KMath performance still be better than natural python, but worse than optimized native/scipy (mostly due to boxing operations on primitive numbers). The best performance of optimized parts should be better than scipy.

Releases

The project is currently in pre-release stage. Work builds could be obtained with .

Contributing

The project requires a lot of additional work. Please fill free to contribute in any way and propose new features.